Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/16329 |
Resumo: | This paper presents a novel adaptive control strategy with rejection ability for unmanned aerial vehicles (UAVs), namely fuzzy model-free control (FMFC). It is based on the model-free control (MFC) concept, where the control parameters are tuned online using fuzzy logic. The controller assumes an ultra-local model that can compensate unknown/unmodelled dynamics, uncertainties and external disturbances, ensuring a good robustness level. Moreover, the fuzzy logic system is used to tune online the proportional-derivative terms due to its heuristic aspect. These compensation and adaptation mechanisms allow ensuring good compromise robustness-performance even in the presence of disturbances. Several experiments, using RotorS Gazebo micro aerial vehicle (MAV) simulator, are provided to demonstrate the effectiveness of the proposed controller compared with other techniques. The fuzzy model-free controller shows superior performance without the time-consuming and tedious tuning task. |
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Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of QuadrotorMicro aerial vehicleMAVModel-free controlMFCFuzzy logicAdaptive controlRobust controlThis paper presents a novel adaptive control strategy with rejection ability for unmanned aerial vehicles (UAVs), namely fuzzy model-free control (FMFC). It is based on the model-free control (MFC) concept, where the control parameters are tuned online using fuzzy logic. The controller assumes an ultra-local model that can compensate unknown/unmodelled dynamics, uncertainties and external disturbances, ensuring a good robustness level. Moreover, the fuzzy logic system is used to tune online the proportional-derivative terms due to its heuristic aspect. These compensation and adaptation mechanisms allow ensuring good compromise robustness-performance even in the presence of disturbances. Several experiments, using RotorS Gazebo micro aerial vehicle (MAV) simulator, are provided to demonstrate the effectiveness of the proposed controller compared with other techniques. The fuzzy model-free controller shows superior performance without the time-consuming and tedious tuning task.Inderscience PublishersRepositório Científico do Instituto Politécnico do PortoChekakta, ZakariaZerikat, MokhtarBouzid, YasserKoubaa, Anis20202119-01-01T00:00:00Z2020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/16329eng2045-106710.1504/IJMA.2020.109058metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T13:03:05Zoai:recipp.ipp.pt:10400.22/16329Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:36:01.291313Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor |
title |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor |
spellingShingle |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor Chekakta, Zakaria Micro aerial vehicle MAV Model-free control MFC Fuzzy logic Adaptive control Robust control |
title_short |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor |
title_full |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor |
title_fullStr |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor |
title_full_unstemmed |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor |
title_sort |
Adaptive Fuzzy Model-free Control For 3d Trajectory Tracking Of Quadrotor |
author |
Chekakta, Zakaria |
author_facet |
Chekakta, Zakaria Zerikat, Mokhtar Bouzid, Yasser Koubaa, Anis |
author_role |
author |
author2 |
Zerikat, Mokhtar Bouzid, Yasser Koubaa, Anis |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Chekakta, Zakaria Zerikat, Mokhtar Bouzid, Yasser Koubaa, Anis |
dc.subject.por.fl_str_mv |
Micro aerial vehicle MAV Model-free control MFC Fuzzy logic Adaptive control Robust control |
topic |
Micro aerial vehicle MAV Model-free control MFC Fuzzy logic Adaptive control Robust control |
description |
This paper presents a novel adaptive control strategy with rejection ability for unmanned aerial vehicles (UAVs), namely fuzzy model-free control (FMFC). It is based on the model-free control (MFC) concept, where the control parameters are tuned online using fuzzy logic. The controller assumes an ultra-local model that can compensate unknown/unmodelled dynamics, uncertainties and external disturbances, ensuring a good robustness level. Moreover, the fuzzy logic system is used to tune online the proportional-derivative terms due to its heuristic aspect. These compensation and adaptation mechanisms allow ensuring good compromise robustness-performance even in the presence of disturbances. Several experiments, using RotorS Gazebo micro aerial vehicle (MAV) simulator, are provided to demonstrate the effectiveness of the proposed controller compared with other techniques. The fuzzy model-free controller shows superior performance without the time-consuming and tedious tuning task. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-01-01T00:00:00Z 2119-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/16329 |
url |
http://hdl.handle.net/10400.22/16329 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2045-1067 10.1504/IJMA.2020.109058 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Inderscience Publishers |
publisher.none.fl_str_mv |
Inderscience Publishers |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799131451016347648 |